Smoothed Complexity of SWAP in Local Graph Partitioning

We give the first quasipolynomial upper bound phi n(polylog(n)) for the smoothed complexity of the SWAP algorithm for local Graph Partitioning (also known as Bisection Width) under the full perturbation model, where n is the number of nodes in the graph and phi is a parameter that measures the magnitude of perturbations applied on its edge weights. More generally, we show that the same quasipolynomial upper bound holds for the smoothed complexity of the 2-FLIP algorithm for any binary Maximum Constraint Satisfaction Problem, including local Max-Cut, for which similar bounds were only known for 1-FLIP. Our results are based on an analysis of a new notion of useful cycles in the multigraph formed by long sequences of double flips, showing that it is unlikely for every double flip in a long sequence to incur a positive but small improvement in the cut weight.